JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, VOL. 118, 5770–5780, doi:10.1002/jgrd.50342, 2013
Atmospheric oxidation chemistry and ozone production: Results
from SHARP 2009 in Houston, Texas
Xinrong Ren,1,2 Diana van Duin,3 Maria Cazorla,3,4 Shuang Chen,3 Jingqiu Mao,5
Li Zhang,3 William H. Brune,3 James H. Flynn,6 Nicole Grossberg,6 Barry L. Lefer,6
Bernhard Rappenglück,6 Kam W. Wong,7,8 Catalina Tsai,7 Jochen Stutz,7 Jack E. Dibb,9
B. Thomas Jobson,10 Winston T. Luke,2 and Paul Kelley2
Received 13 November 2012; revised 5 March 2013; accepted 17 March 2013; published 7 June 2013.
[1] Ozone (O3) and secondary fine particles come from the atmospheric oxidation
chemistry that involves the hydroxyl radical (OH) and hydroperoxyl radical (HO2), which
are together called HOx. Radical precursors such as nitrous acid (HONO) and
formaldehyde (HCHO) significantly affect the HOx budget in urban environments. These
chemical processes connect surface anthropogenic and natural emissions to local and
regional air pollution. Using the data collected during the Study of Houston Atmospheric
Radical Precursors (SHARP) in spring 2009, we examine atmospheric oxidation chemistry
and O3 production in this polluted urban environment. A numerical box model with five
different chemical mechanisms was used to simulate the oxidation processes and thus OH
and HO2 in this study. In general, the model reproduced the measured OH and HO2 with all
five chemical mechanisms producing similar levels of OH and HO2, although midday OH
was overpredicted and nighttime OH and HO2 were underpredicted. The calculated HOx
production was dominated by HONO photolysis in the early morning and by the photolysis
of O3 and oxygenated volatile organic compounds (OVOCs) in the midday. On average,
the daily HOx production rate was 24.6 ppbv d1, of which 30% was from O3 photolysis,
22% from HONO photolysis, 15% from the photolysis of OVOCs (other than HCHO),
14% from HCHO photolysis, and 13% from O3 reactions with alkenes. The O3 production
was sensitive to volatile organic compounds (VOCs) in the early morning but was sensitive
to NOx for most of afternoon. This is similar to the behavior observed in two previous
summertime studies in Houston: the Texas Air Quality Study in 2000 (TexAQS 2000) and
the TexAQS II Radical and Aerosol Measurement Project in 2006 (TRAMP 2006). Ozone
production in SHARP exhibits a longer NOx-sensitive period than TexAQS 2000 and
TRAMP 2006, indicating that NOx control may be an efficient approach for the O3 control
in springtime for Houston. Results from this study provide additional support for
regulatory actions to reduce NOx and reactive VOCs in Houston in order to reduce O3 and
other secondary pollutants.
Citation: Ren, X., et al. (2013), Atmospheric oxidation chemistry and ozone production: Results from SHARP 2009 in
Houston, Texas, J. Geophys. Res. Atmos., 118, 5770–5780, doi:10.1002/jgrd.50342.
1
Rosenstiel School of Marine and Atmospheric Science, University of
Miami, Miami, Florida, USA.
2
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, Maryland, USA.
3
Department of Meteorology, Pennsylvania State University, University
Park, Pennsylvania, USA.
Corresponding author: X. Ren, Air Resources Laboratory, National
Oceanic and Atmospheric Administration, College Park, MD, USA.
([email protected])
©2013. American Geophysical Union. All Rights Reserved.
2169-897X/13/10.1002/jgrd.50342.
4
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard
Space Flight Center, Greenbelt, Maryland, USA.
5
Geophysical Fluid Dynamics Laboratory, National Oceanic and
Atmospheric Administration, Princeton, New Jersey, USA.
6
Department of Earth and Atmospheric Sciences, University of
Houston, Houston, Texas, USA.
7
Department of Atmospheric and Oceanic Sciences, University of
California at Los Angeles, Los Angeles, California, USA.
8
Jet Propulsion Laboratory, National Aeronautics and Space
Administration Pasadena, California, USA.
9
Climate Change Research Center, Institute for the Study of Earth, Oceans
and Space, University of New Hampshire, Durham, New Hampshire, USA.
10
Department of Civil and Environmental Engineering, Washington
State University, Seattle, Washington, USA.
5770
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
Figure 1. A simplified schematic diagram showing atmospheric oxidation chemistry in which OH and HO2 play central
roles in the processes producing secondary pollutants such as
ozone and fine particles.
1.
Introduction
[2] The chemistry of atmospheric radicals, especially the
hydroxyl radical (OH) and hydroperoxyl radical (HO2),
collectively called HOx, is deeply involved in the formation
of secondary pollutants such as ozone (O3) and fine particles
(Figure 1). The photolysis of O3, nitrous acid (HONO),
formaldehyde (HCHO), hydrogen peroxide (H2O2), and
some oxygenated volatile organic compounds (OVOCs) is
the initial source for OH and HO2 radicals. OH initiates
most reaction sequences that cycle surface emissions
through the atmosphere and react with carbon monoxide
(CO) and formaldehyde to produce HO2. In turn, HO2 reacts
with nitric oxide (NO) to reproduce OH, thus creating a HOx
cycle. OH also oxidizes nitrogen dioxide (NO2) and sulfur
dioxide (SO2) to produce nitrate and sulfate, two main
components of aerosols, and volatile organic compounds
(VOCs) to produce organic peroxy radicals, RO2. Both
HO2 and RO2 oxidize NO to produce NO2, without
destroying O3, and the subsequent photolysis of NO2
produces O3 (Figure 1).
[3] Understanding these chemical processes is important
in determining the extent and types of emission reductions
that are most effective in reducing O3. Predictive capability
for O3 and its response to regulatory action also requires a
firm understanding of HOx sources, sinks, and interactions
with anthropogenic hydrocarbons and nitrogen oxides. In
urban environments like Houston, radical precursors such
as nitrous acid (HONO) and formaldehyde (HCHO) can
significantly affect the HOx budget [Olaguer et al., 2009;
Mao et al., 2010]. These chemical processes connect surface
emissions, both human and natural, to local and regional
pollution.
[4] Although portions of the chemistry that lead to the
formation of O3 have been understood for decades, new
discoveries have revealed the need to improve scientific
understanding and detailed mechanisms of O3 formation
chemistry [Volz-Thomas et al., 2003; Texas Air Quality
Research Program, 2010]. Radical production in Houston
and some other urban areas appears to be underestimated
by chemical mechanisms [Olaguer et al., 2009]. Some gasphase and heterogeneous chemical reactions seem to be
missing from the mechanisms, e.g., a missing heterogeneous
source of HONO which in turn could be an important OH
source. Further, the roles of some radical precursors such
as HONO and HCHO in O3 formation in urban environments have not been well quantified [Texas Air Quality
Research Program, 2010].
[5] In summer 2000, the Texas Air Quality Study campaign (TexAQS 2000) was conducted in Eastern Texas.
The study revealed that the Greater Houston Area often
encountered critical loadings of a variety of species and
the rapid O3 formation processes appeared to be associated
with releases of highly reactive VOCs from industrial
facilities [Lefer and Rappengluck, 2010]. The meteorological conditions in Houston were also found to promote O3
formation [Berkowitz et al., 2004]. In summer 2006 within
the TexAQS-II efforts, the TexAQS-II Radical and Aerosol
Measurement Project (TRAMP 2006) was conducted at the
Moody Tower site on the campus of the University of
Houston. TRAMP 2006 found that nitrous acid (HONO)
exceeded 2 ppbv close to sunrise and remained at hundreds
of pptv during the day and strong vertical gradients indicate
ground-level source of HONO [Stutz et al., 2010a]. Photolysis
of HONO and HCHO was an important HOx source [Mao
et al., 2010]. Ozone production rates were often greater
than 40 ppbv h1, and a high OH chain length (10–20) was
associated with high VOC abundances in Houston [Mao
et al., 2010].
[6] Following TexAQS 2000 and TRAMP 2006, the
Study of Houston Atmospheric Radical Precursors
(SHARP) in spring 2009 aimed to investigate sources of
important radical precursors like HONO and HCHO and to
reduce uncertainties in photochemical processes and thus
to improve our ability to model radicals and ozone formation. In this study, the instrument suite measured the most
important contributions to O3 and particle formation and
thus enabled a thorough analysis of the atmospheric chemistry and O3 formation in Houston. This analysis has the
potential to improve the understanding of atmospheric oxidation in Houston and perhaps other urban areas. Such an
improved understanding could aid the development of the
State Implementation Plan (SIP) for Houston, which is essential for the future primary and secondary National Ambient Air
Quality Standards for O3 proposed by U.S. Environmental
Protection Agency (EPA) to be met there.
2.
Measurement and Model Description
2.1. Site
[7] The SHARP campaign (15 April to 31 May 2009) was
designed to examine the processes involved in the springtime O3 peak observed in southeast Texas. Chemical and
meteorological measurements were made from a height of
70 m above ground level at the top of a 10 m tower on a roof
balcony of the north Moody Tower, an 18-story dormitory
on the campus of the University of Houston. The campus
is located 35 km west of Galveston Bay, 70 km northwest
of Galveston, Texas, and the Gulf of Mexico. The north
Moody Tower (29.7176 N, 95.3413 W) is located in a
partially wooded and grass covered land surface approximately 5 km southeast of tall buildings in downtown Houston,
1 km southwest of Interstate 45, and 3.5 km north of the
South Interstate 610 Loop. The measurement site is 6 km
southwest of the Buffalo Bayou Turning Basin and 25 km
5771
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
Table 1. Meteorological Parameters and Gas-Phase Chemical Species Measured During SHARP
Analyte*
Instrument
Uncertainty (1s)
Interval
Campbell research meteorological system
~ 5%
60 s
Scanning actinic flux spectrometer
Thermo 49c, 48c-TLE, 42c-TL with NOxy inlet
(Blue Light and Mo converters)
Perkin-Elmer GC-FID
~ 10%
~ 5–10%
60 s
60 s, 5 min
~ 5–10%
1h
HNO3, HONO, HCl
HONO
OH, HO2, OH reactivity
Mist Chamber/IC
Liquid coil scrubbing/UV-VIS absorption
Laser-induced fluorescence
5%
8%
20%
5 min
2 min
2 min
Ozone production rate
O3, NO2, SO2, HCHO, HONO, NO3
OVOCs, HCHO, isoprene, aromatics
Measurement of ozone production sensor
Long-path DOAS
PTR-MS
~ 15%
3–5%
5%
10 min
Variable
60 s
Meteorology (T, P, RH, wind, rain,
cloud camera)
Photolysis rate coefficients
Basic trace gases (O3, CO, SO2,
NO, NO2, NOy)
VOCs (C2-C10 NMHCs)
Reference
Lefer et al. [2010]
Lefer et al. [2010]
Lefer et al. [2010]
Luke et al. [2010]
Leuchner and
Rappenglück [2010]
Stutz et al. [2010a]
Ren et al. [2010]
Faloona et al. [2004]
Mao et al. [2009]
Cazorla et al. [2012]
Stutz et al. [2010b]
Jobson et al. [2005]
*Only the measurements used in this work are listed here.
west-southwest of the San Jacinto Battleground Monument,
the western and eastern edges, respectively, of the petrochemical facilities in the Houston Ship Channel. The elevated
location of the site is unique because other surface sampling
sites are usually much more sensitive to the nearby (i.e., within
100 m) local activities such as traffic, parking lots, delivery
trucks, railways, and nocturnal surface drainage.
2.2. Measurements
[8] The suite of measurements during SHARP 2009 was
extensive and included measurements of meteorological
parameters, actinic fluxes, inorganic trace gases, VOCs, radicals, and oxygenated species (Table 1). All measurements
were recorded with synchronized timestamps and were
matched with corresponding meteorological parameters.
Some key measurements in this study include O3 production
rate measured by the Measurement of Ozone Production
Sensor (MOPS) [Cazorla and Brune, 2010] and OH and
HO2 radicals measured with laser-induced fluorescence
(LIF) spectroscopy at low pressure, often called Fluorescence Assay in a Gas Expansion (FAGE) [Hard et al.,
1984; Faloona et al. 2004]. As described by Mao et al.
[2012], two approaches were adopted for measuring OH
with LIF during SHARP 2009: the traditional wavelength
modulation method (called “OHwave”) and the chemical
modulation method (called “OHchem”). Because OHwave
likely contains certain interferences related to oxidation
products of biogenic VOCs [Mao et al., 2012], OHchem
was used as measured OH in this study.
[9] Laboratory studies also found that the HO2 measurements in some FAGE-type instruments are susceptible to
interference from RO2 species that come from alkenes and
aromatics [Fuchs et al., 2011; Mao et al., 2012]. A laboratory study showed that our LIF instrument was also affected
by the same interference. Compared to HO2, the relative
sensitivities for RO2 are 1.20 for isoprene, 0.98 for ethene,
0.44 for limonene, 0.41 for cyclohexane, 0.40 for a-pinene,
and 0.32 for b-pinene. With these measurements, the relative
sensitivities for RO2 derived from other alkenes and
aromatics were extrapolated using the model to simulate
the conversion of RO2 to OH in our HO2 detection cell.
The measured HO2 concentrations were corrected for this
artifact by subtracting the product of each RO2 concentration
calculated in the model and its relative sensitivity from the
measured HO2 wave. The corrected measured HO2 is used
in the following analysis. This correction reduces the HO2
measurements by 16% on average.
[10] The absolute uncertainty of the GTHOS measurement
of OH and HO2 determined from calibrations is 32% at the
2s confidence level [Faloona et al., 2004]. In addition, the
uncertainty of the chemical removal method used to measure
OHchem is estimated to be about 20 % (2s confidence),
so the combined absolute uncertainty for OHchem is about
38% (2s confidence). The correction of alkene-based
RO2 interference increases the HO2 measurement uncertainty. With a typical midday radical mixing ratio of 20 pptv
for measured HO2 and 1.3 pptv for an interfering HO2 level
from alkene-based RO2, the propagation uncertainty of real
HO2 is 34% (2s confidence) for midday conditions. At
night, the 2s uncertainty of real HO2 slightly increases to
36% with an averaged HO2 mixing ratio of 5.6 pptv and
an interfering HO2 level of 0.46 pptv.
2.3. Model Description
[11] A box model was constructed using existing
mechanisms to calculate radical formation rates and radical
concentrations. Both highly explicit and condensed chemical
mechanisms were used in the box model to examine the
consistency of these mechanisms with each other and of
the mechanisms with measurements. The box model was
run with the FACSIMILE software for Windows (MCPA
Software), which has been successfully used in the modeling
efforts for some previous research projects [e.g., Chen et al.,
2010; Mao et al., 2010].
[12] Five photochemical mechanisms were used in this
study: the Regional Atmospheric Chemical Mechanism
Version 2 (RACM2) [Goliff et al., 2013], the Carbon Bond
Mechanism Version 2005 (CB05) [Yarwood et al., 2005],
the Statewide Air Pollution Research Center mechanism
Version 2007 (SAPRC-07) [Carter, 2007], the NASA
Langley Research Center mechanism (LaRC) [Crawford
et al., 1999; Olson et al., 2004], and the Master Chemical
Mechanism (MCM v3.1) [Jenkin et al., 2003; Saunders
et al., 2003; Bloss et al., 2005]. These mechanisms are well
known and have been actively in use in research and regulatory applications. The original mechanisms were used, while
kinetic data were updated based on the most recent chemical
kinetic data evaluations [e.g., Sander et al., 2011].
[13] In order to run the box model with different chemical
mechanisms, measurements including measured long-lived
5772
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
OH (pptv)
0.8
0.6
0.4
0.2
0
obs
mod
HO2 (pptv)
60
40
20
0
4/30
5/5
5/10
5/15
5/20
5/25
5/30
Day of year (CST)
Figure 2. Time series of measured (red) and modeled (blue) OH (top) and HO2 (bottom) mixing ratios
during SHARP. Data are averaged in 1 h intervals. The modeled OH and HO2 were the averaged simulations from the five mechanisms.
inorganic and organic compounds and meteorological
parameters (temperature, pressure, humidity, and photolysis
frequencies) were averaged into 10 min values that became
the model input. Nitric oxide (NO) was measured during
SHARP 2009 and was treated as a long-lived inorganic
species to constrain the model. Species like HONO and
HCHO were measured both locally by individual instruments
on Moody Tower and by Long-Path DOAS (LP-DOAS) along
the path between the Moody Tower and Downtown Houston.
Because most model input parameters were measured on the
Moody Tower, the measurements on the Moody Tower were
used in the model. The HONO measurements by the liquid
coil scrubbing/UV-VIS instrument were mainly used in the
model because of its better time resolution with some measurement gaps filled by the MC/IC HONO measurements. For
each data point, the model was run for 24 h, long enough to
allow most calculated reactive intermediates to reach steady
state but short enough to prevent the buildup of secondary
products. A deposition lifetime of two days was assumed for
all calculated species to avoid unexpected accumulation of
these species in the model. Model sensitivity runs show that
by increasing or decreasing this deposition lifetime by a factor
of 10, i.e., ~5 h and 20 days, the corresponding changes in the
modeled OH and HO2 concentrations are less than 3%. At the
end of 24 h, the model generated time series of OH, HO2, RO2,
and other reactive intermediates.
[14] It is worth noting that the zero-dimensional (box)
model simulations did not include advection and emissions, although advection and emissions are certainly
important factors for the air pollution formation. The
primary goal of this study is to understand the radical
behavior. Most radicals of interest have very short lifetimes
of seconds or less, and all of the long-lived radical
precursors and O3 precursors were measured and used to
constrain the box model calculations. Thus, advection and
emissions can be neglected for this study of radicals and
their production and loss rates.
[15] Uncertainties in the model calculations were estimated to be 52% for OH and 61% for HO2 both at
the 2s confidence level based on Monte Carlo method by
applying uncertainties of kinetic rate coefficients [e.g.,
Sander et al., 2011] and of measurements used to constrain
the models [Chen et al., 2010].
3.
Results
3.1. Comparison of Modeled and Measured OH and HO2
[16] The measured and modeled OH and HO2 exhibit
similar diurnal and day-to-day variations, with maxima in
the midday and minima at night (Figures 2 and 3). Both
the measured and modeled OH peaks occurred at around
local solar noon, while the measured and modeled HO2
peaks appeared in the early afternoon (Figure 3).
[17] In general, the model reproduced the measured OH
and HO2. All five mechanisms produced similar levels of
OH and HO2, although CB05 produced slightly more HOx
than others. The differences among the five mechanisms
are mainly due to different treatments of VOCs. Midday
OH was overpredicted, while nighttime OH and HO2 were
underpredicted. Comparing measured OH and HO2 to the
averaged model values with the five mechanisms, the
median daytime measured-to-modeled OH ratio is 0.90 and
the median daytime measured-to-modeled HO2 ratio is
1.22. The model underpredicted nighttime HOx with a
median measured-to-modeled OH ratio of 6.34 and a median
measured-to-modeled HO2 ratio of 1.73, indicating that
either HOx sources or sinks are incomplete or incorrect in
the model mechanisms.
[18] Using the composite diurnal values in 1 h bins,
independent-sample t-tests (Student’s t-tests) were
conducted to see if there are significant differences between
the measurements and model calculations. A t-test result
with a p-value (significance) greater than 0.05 is considered
to be not significantly different between the two samples.
5773
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
Interfering [OH] (pptv)
OH (pptv)
0.6
0.4
0.2
0
obs
0.4
0.2
0
-0.2
RACM2
Interfering [HO2] (pptv)
CB05
40
LaRC
HO2 (pptv)
SAPRC07
30
MCM
20
10
0
0:00
6:00
12:00
18:00
0:00
Time of day (CST)
10
5
0
-5
0:00
6:00
12:00
18:00
0:00
Time of day (CST)
Figure 3. Median diurnal variations of measured and modeled OH (upper-left panel) and HO2 (bottomleft panel) mixing ratios and interfering OH (top-right panel) and HO2 (bottom-right) during SHARP.
Modeled OH and HO2 were calculated from five different chemical mechanisms, including RACM2,
CB05, LaRC, SAPRC-07, and MCM. Observed OH and HO2 data are limit to the periods when the
modeled data are available. Error bars on the left panels represent the absolute uncertainties of the OH
and HO2 measurements. Error bars on the right panels are the standard deviations of the interfering OH
and HO2 in hourly bins.
The t-test results for the measured and modeled OH show
that the p-values are 0.80 for RACM2, 0.49 for CB05,
0.98 for LaRC, 0.91 for SAPRC-07, and 0.75 for MCM.
The results for the measured and modeled HO2 show the
p-values of 0.10 for RACM2, 0.83 for CB05, 0.12 for LaRC,
0.52 for SAPRC-07, and 0.09 for MCM. All these t-tests
were conducted at a 95% confidence level and suggest no
significant statistical difference between the measurements
and model calculations. On the other hand, the nighttime
differences for OH are significant.
3.2. Nighttime HOx
[19] Studies have found that there are two oxidation
pathways that can produce HOx at night: O3 reactions with
alkenes and the nitrate radical (NO3) chemistry [FinlaysonPitts and Pitts, 2000; Monks, 2005]. The ozone-alkene
chemistry involves the ozone addition to the double carbon
bond to form a primary ozonide, which then rapidly decomposes to a vibrationally excited carbonyl oxide (Criegee
intermediate) and carbonyl products. The produced Criegee
intermediate then further decomposes to produce OH and
RO2 [Monks, 2005]. The nitrate radical can react with a few
VOCs such as HCHO, unsaturated aldehydes, methacrolein,
and glyoxal to produce HOx and RO2. These processes
become important for the nighttime HOx production due to
lack of photolytic HOx sources at night.
[20] Mean measured nighttime OH was 0.041 pptv or
1.0 106 molecules cm3, while the modeled nighttime
OH concentration (the averaged value of the five mechanisms) was only 0.0071 pptv or 1.7 105 molecules cm3
(Figure 3). The estimated OH detection limit was about
0.01 pptv, and the measurement uncertainty was about
40% at the 2s confidence level. In our previous studies,
OHwave was used, which is now known to have a possible
interference in the presence of O3 and alkenes. In this study,
we use OHchem, which appears to have no interference
[Mao et al., 2012]. On average, OHchem is on average
0.70 of OHwave during the day and 0.50 at night during
SHARP 2009. Further laboratory studies show that the
interfering internal OH is made primarily near and in the
OH detection cell [Mao et al., 2012].
[21] The mean measured nighttime HO2 was 6.7 pptv,
while the mean modeled nighttime HO2 concentration
(the averaged value of the five mechanisms) was 3.3 pptv
(Figure 3). The model underpredicted nighttime OH significantly (Figure 3), indicating that the importance of OH in the
nighttime oxidation chemistry may be underestimated. The
median measured-to-modeled HO2 ratio at night was 1.73,
which is marginally greater than the combined uncertainty
of measured and modeled HO2 (70%, 2s). The median
measured-to-modeled OH ratio at night was 6.3, which is
significantly beyond the combined uncertainty of measured
and modeled OH (64%, 2s). These differences indicate
that all mechanisms fail to capture the processes that create
nighttime OH and HO2 in this urban environment.
[22] Possible reasons for the discrepancy between the
observed and modeled night HOx include the missing
mechanisms that can produce significant nighttime HOx. For
example, a recent chamber study found significant OH production from the NO3-initiated oxidation of isoprene through
RO2 + HO2 reactions and oxidation of nitrooxyhydroperoxide
[Kwan et al., 2012]. A few recent studies also suggested that
the photooxidation of isoprene can regenerate OH either
through isomerization of isoprene peroxy radicals [Peeters
5774
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
HO2 /OH ratio
obs/mod HO2
obs/mod OH
10
1
0.1
10
1
0.1
1000
obs
mod
100
10
1
0.1
1
10
20
[NO] obs (ppbv)
Figure 4. The ratios of measured-to-modeled OH (top),
HO2 (middle), and HO2/OH (bottom) as a function of NO
mixing ratio. Dots are all 10 min average data with O3 photolysis frequency, J(O1D), greater than 1.0 105 s1.
Linked symbols show the median values in the log(NO)
bins.
et al., 2009; Peeters and Müller, 2010] or the formation of
epoxides [Paulot et al., 2009; Crounse et al., 2011]. Although
this later mechanism is OH initiated and mainly proposed for
daytime, it can also contribute to nighttime OH production if
the oxidation of isoprene through its reaction with OH is
significant at night. Apparently further investigation is needed
in order to examine possible incomplete or incorrect understanding of atmospheric chemistry in the model that is responsible for the discrepancies.
3.3. Daytime NO Dependence
[23] The measured-to-modeled OH and HO2 ratios and
their NO dependence can test our understanding of HOx
photochemistry. In polluted environments, the cycling
between OH and HO2 is very fast because of existing high
levels of NO which reacts with HO2 to produce OH and
NO2 and thus determine the photochemical equilibrium
between OH and HO2 (Figure 1). In order to avoid the
confusion of two different effects—the poorly known and
dominant O3 + alkene HOx source at night and the NO effect
on HOx chemistry during the day—for the NO dependence
analysis, we limit the data to daytime when O3 photolysis
frequency, J(O1D), was greater than 1.0 105 s1
(corresponding to a period approximately from 8:00 to
~16:00, Central Standard Time) so that the photochemistry
is dominant.
[24] The model predicted OH generally well when NO is
less than ~3 ppbv and slightly underpredicted OH when
NO is greater than ~3 ppbv (Figure 4, top). This reasonably
good agreement between observed and modeled OH at low
NO levels is consistent with a few previous studies [Ehhalt,
1999; Kanaya et al., 2007] in polluted environments but
different from some recent studies in VOC-rich and low
NOx environments [e.g., Ren et al., 2008; Lelieveld et al.,
2008; Hofzumahaus et al., 2009; Whalley et al., 2011;
Lu et al., 2012, 2013], where biogenic emissions are dominant. This difference is most likely due to the unique chemical
conditions in Houston, where VOCs are mainly from anthropogenic emissions. For HO2, the measured-to-modeled ratio
is close to 1 and fairly constant when NO is below 1 ppbv,
while the ratio then increases as NO increases (Figure 4, middle). This higher-than-expected HO2 at high NO levels in this
study is consistent with results from some previous studies in
urban and suburban environments [e.g., Konrad et al., 2003;
Martinez et al., 2003; Ren et al., 2003a, 2003b; Ren et al.,
2005; Kanaya et al., 2007; Ren et al., 2008; Dusanter et al.,
2009; Lu et al., 2012, 2013].
[25] Both the measured and modeled HO2/OH ratios
decrease with increasing NO level (Figure 4, bottom)
because of the NO reaction with HO2 to shift HOx into OH
by reacting with HO2. The agreement between measured
and modeled HO2-to-OH ratios is good when NO mixing
ratios are less than 1 ppbv, while the difference between
measured and modeled HO2/OH increases as NO further
increases. The slope of the measured HO2/OH as a function
of NO is slightly less than the modeled slope. This difference is consistent with the measured HO2 being greater than
the modeled HO2 at high NO. The NO dependence of the
measured and modeled HO2/OH ratios is also consistent
with results from several previous studies in urban environments [e.g., Ren et al., 2003a; Ren et al., 2005; Chen et al.,
2010; Kanaya et al., 2012].
4.
Discussion
4.1. HOx Budget
[26] A number of urban studies have found significant
daytime HONO and OVOCs that can be photolyzed to produce OH and HO2 radicals [e.g., Ren et al., 2003a; Olaguer
et al., 2009; Mao et al., 2010; Liu et al., 2012]. Other major
processes of primary HOx production includes O3 photolysis, the reaction of O(1D) with H2O, and O3 reactions with
alkenes. Major HOx loss processes includes the OH reaction
with NO2 and the reactions among OH, HO2, and RO2.
[27] During SHARP, the calculated HOx production was
dominated by HONO photolysis in the early morning and
by the photolysis of O3 and OVOC in the midday (Figure 5).
At night, HOx production was mainly from O3 reactions with
alkenes. On average, the daily HOx production rate was 24.6
ppbv d1, of which 30% was from O3 photolysis, 22% from
HONO photolysis, 15% from the photolysis of OVOCs
(other than HCHO), 14% from HCHO photolysis, and
13% from O3 reactions with alkenes. For HOx loss, the
clearly dominant process was the OH reaction with NO2,
while the self-reactions among OH, HO2, and RO2 became
important in the afternoon when these radicals reached their
highest values.
[28] The importance of HONO and OVOC photolysis
to HOx production is consistent with some recent studies
in urban and suburban environments [Alicke et al., 2003;
Dusanter et al., 2009; Volkamer et al., 2010; Liu et al.,
2012]. For instance, Dusanter et al. [2009] found that
HONO photolysis contributed 35% of daytime HOx
production in Mexico City during MCMA 2006, while
Alicke et al. [2003] found that HONO photolysis contributed
5775
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
NO3 to produce OH and HO2. Overall O3 + alkene reactions
contributed about 84 pptv h1 or 68% to the nighttime
HOx production, while NO3 chemistry contributes about
39 pptv h1 or 32% (Figure 6).
1
0.1
4.2. O3 Production Rate and Its Sensitivity to NOx
and VOCs
[30] During the day, the photochemical O3 production
rate is essentially the production rate of NO2 molecules
from HO2 + NO and RO2 + NO reactions [Finlayson-Pitts
and Pitts, 2000]. The net instantaneous O3 production rate,
P(O3), can be written approximately as the following
equation:
0.01
L(HOx) (ppbv h-1)
0.001
10
1
PðO3 Þ ¼ kHO2 þNO ½HO2 ½NO þ
0.1
0.001
0:00
X
kRO2i þNO ½RO2i ½NO
kOHþNO2 þM ½OH½NO2 ½M PðRONO2 Þ
0.01
6:00
12:00
18:00
Time of day (CST)
kHO2 þO3 ½HO2 ½O3 kOHþO3 ½OH½O3 kOð1 D ÞþH 2 O O 1 D ½H 2 O LðO3 þ alkenesÞ
0:00
Figure 5. Diurnal median variations of HOx production
(top) and HOx loss (bottom) in the model calculation. HOx
production processes include O3 photolysis followed by
the O(1D) + H2O reaction, the photolysis of OVOCs (other
than HCHO), HONO photolysis, HCHO photolysis (the radical producing pathway), and O3 reactions with alkenes.
HOx loss processes include OH reaction with NOx, HO2
self-reaction, and HO2 + RO2 reactions.
up to 20% of the total OH formed in a 24 h period during
BERLIOZ. Liu et al. [2012] found that the photolysis of
OVOCs was the primary ROx (= OH + HO2 + RO2) source
with comparable contribution from the HONO photolysis
in Beijing during CAREBeijing-2007, while Volkamer
et al. [2010] found that OVOCs contributed about half of
the daytime radical production in Mexico City during
MCMA 2003.
[29] As discussed previously, two different pathways can
contribute to nighttime HOx production: O3 reactions with
alkenes and NO3 reactions with VOCs. Typical diurnal
variations of HOx production from these two pathways show
that HOx production from O3 + alkene reactions peaked in
the midday when O3 concentrations were the highest, while
HOx production from NO3 chemistry peaked at night
because of low NO3 concentrations during the day due to
its fast photolysis (Figure 6). Measurements made by the
long-path Differential Optical Absorption Spectrometer
(LP-DOAS) during SHARP confirm that there were significant nighttime NO3 levels away from the surface where
low nighttime NO levels were observed. During SHARP,
the average observed nighttime (from 6 P.M. to 6 A.M.,
Central Standard Time) NO3 mixing ratio was 2.8 1.1 pptv
and the average modeled nighttime NO3 mixing ratio was
2.6 1.1 pptv, indicating good agreement between the
observed and modeled NO3 mixing ratios. The average
nighttime ozone mixing ratio was 36 19 ppbv. Using the
RACM2 mechanism, HOx production rates from O3 +
alkenes and NO3 chemistry were calculated based on both
observed and calculated VOCs that can react with O3 and
(1)
where k terms are the reaction rate coefficients. The negative
terms in equation (1) correspond to the reaction of OH and
NO2 to form nitric acid, the formation of organic nitrates,
P(RONO2), the reactions of OH and HO2 with O3, the
photolysis of O3 followed by the reaction of O(1D) with
H2O, and O3 reactions with alkenes. As shown in Figure 7,
these negative terms are relatively small compared to the P
(O3) from HO2 + NO and RO2 + NO reactions. Note that only
photochemical production and loss terms are included and
ozone deposition term is excluded in equation (1) in order to
compare it with the measurement by MOPS, which does not
account for ozone deposition. Because we mainly focus on
photochemical O3 production, the advection and dry deposition terms are not included in equation (1), although they are
important factors affecting ambient O3 levels but not the O3
production rate. The estimated uncertainty of P(O3) measured
by MOPS is 30% at the 2s confidence level and 10 min integration time [Cazorla et al., 2012]. The overall uncertainty
of calculated P(O3) is about 66% (2s).
0.25
0.2
P(HOx) (ppbv h-1)
P(HOx) (ppbv h-1)
10
0.15
O3 + alkenes
0.1
NO3 chem
0.05
0
0:00
6:00
12:00
18:00
0:00
Time of day (CST)
Figure 6. Median diurnal variations of HOx production in
the model calculation from O3 + alkenes reactions and from
NO3 chemistry. Modeled NO3 was used in the calculation
due to low data coverage of the DOAS-measured NO3.
Shaded areas indicate the nighttime periods.
5776
30
30
25
25
20
20
P(O3) (ppbv hr-1)
P(O3) (ppbv hr-1), [NO] (ppbv)
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
15
10
15
10
5
5
0
0
6:00
12:00
18:00
Time of day (CST)
6:00
12:00
18:00
Time of day (CST)
Figure 7. Left: median diurnal variations of total O3 production rate in the model, P(O3)mod, O3 production rate calculated from the measured HO2, O3 production rate calculated from the modeled HO2,
2
PðO3 ÞHO
mod , and O3 production rate measured by the Measurement of Ozone Production Sensor (MOPS),
P(O3)MOPS, as well as NO mixing ratio. Right: median diurnal variation of the modeled P(O3) and the major contributions to P(O3) from terms in equation (1).
[31] During SHARP, the modeled P(O3) peaked around
noon with the average value of 18 ppbv h1 (Figure 7),
although on a few individual days values as high as
100 ppbv h1 were observed. Based on the model calculations, the cumulative P(O3) was 126 ppbv d1, in which
about 68 ppbv d1 was attributed to the P(O3) from the
2
modeled HO2 reaction with NO, designated as PðO3 ÞHO
mod .
The cumulative P(O3) from the measured HO2 alone,
1
2
designated as PðO3 ÞHO
obs , was about 97 ppbv d . The differHO2
2
ence between PðO3 ÞHO
obs and P ðO3 Þmod mainly appeared in
the morning, when NO levels were high, while in the afterHO2
2
noon, PðO3 ÞHO
obs and PðO3 Þmod agree pretty well (Figure 7).
2
[32] The cumulative difference between PðO3 ÞHO
obs and
HO2
PðO3 Þmod results in a difference of 29 ppbv O3 per day.
Similar results were observed in a few previous studies in
urban environments [e.g., Martinez et al., 2003; Ren et al.,
2003a]. Studies also found that in the troposphere, the
observed HO2-to-RO2 ratio is roughly constant under a
certain environment and has been generally well reproduced
by model calculations in various environments [e.g., Cantrell
et al., 2003; Mihelcic et al., 2003; Ren et al., 2003b]. So in
general, HO2 and RO2 both contribute significantly to ozone
production through their reactions with NO. If we assume that
2
PðO3 ÞHO
obs is 54% of total O3 production, as derived from the
2
model, then PðO3 ÞHO
obs suggests that the actual total O3 production would be 179 ppbv d1, a factor of 1.4 higher than the
cumulated P(O3) in the model. This difference is roughly
consistent with the measured-to-modeled ratio (1.3) of the
cumulative O3 production, where the O3 production rate was
measured directly by the Measurement of Ozone Production
Sensor (MOPS), independent of the OH and HO2 measurements [Cazorla et al., 2012].
[33] Ozone production depends directly on NO concentration and P(HOx) rate [Ren et al., 2003a]. In the model,
2
PðO3 ÞHO
mod reaches the maximum when NO is around 1 ppbv
and then decreases as NO further increases (Figure 8).
However, because measured HO2 does not decrease as much
2
as expected at higher NO levels (Figure 4), PðO3 ÞHO
obs does
not decrease as much as the model predicted (Figure 8). As
HO2
2
a result, the PðO3 ÞHO
obs to PðO3 Þmod ratio increases as NO
increases at high NO levels. This is roughly consistent
with the NO dependence of the ratio of the MOPS measured
P(O3) to the modeled P(O3), although with less NO dependence (Figure 8).
[34] The dependence of O3 production on NOx and VOCs
can be categorized into two typical scenarios: NOx sensitive
and VOC sensitive. As in a previous study [Mao et al.,
2010], we use the method proposed by Kleinman [2005] to
evaluate the O3 production sensitivity using the ratio of
LN/Q, where LN is the radical loss via the reactions with
NOx and Q is the total primary radical production. Because
the radical production rate is approximately equal to the radical loss rate, this LN/Q ratio represents the fraction of radical
loss due to NOx. It was found that when LN/Q is significantly
less than 0.5, the atmosphere is in a NOx-sensitive regime,
and when LN/Q is significantly greater than 0.5, the atmosphere is in a VOC-sensitive regime [Kleinman et al.,
2001; Kleinman, 2005]. Note that the contribution of organic
nitrates impacts the cut-off value for LN/Q to determine the
ozone production sensitivity to NOx or VOCs, and this value
may vary slightly around 0.5 in different environments.
[35] During the springtime SHARP campaign, the O3
production sensitivity to NOx or VOCs had a similar behavior as for two previous summertime studies in Houston,
TexAQS 2000 and TRAMP 2006. P(O3) was VOC sensitive
in the early morning but became more NOx sensitive
throughout the afternoon (Figure 9). These results are independent of the differences between the measured and
modeled OH and HO2. Note that in the afternoon, the O3
production sensitivity during SHARP experienced a longer
NOx-sensitive period than TexAQS 2000 and TRAMP
2006, indicating that NOx control may be a more efficient
approach than VOC control for the O3 control in the
5777
obs/mod P(O3)HO2
HO2 (ppb/hr)
P(O3)mod
HO2 (ppb/hr)
P(O3)obs
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
100
appeared in the late morning and early afternoon, about 3 h
later than that for the days with O3 mixing ratios less than
50 ppbv (Figure 9).
10
1
5.
0.1
100
10
1
0.1
10
1
0.1
0.01
0.1
1
10
100
[NO] (ppbv)
Figure 8. Ozone production rate calculated from measured
2
HO2, PðO3 ÞHO
from
obs (top), O3 production rate calculated
2
2
modeled HO2, PðO3 ÞHO
(middle), and the PðO3 ÞHO
-tomod
obs
HO2
PðO3 Þmod ratio (bottom) as a function of NO. Blue dots are
all 10 min average data. Linked circles show the median
values in the log(NO) bins. Also shown in the bottom panel
is the ratio of the MOPS measured P(O3) to the model P(O3)
as a function of NO (linked squares).
springtime for Houston. This is confirmed by the cumulated
O3 production from the MOPS measurements, in which
112 ppbv of O3 was produced in the NOx sensitive regime
while only 53 ppbv of O3 was produced in the VOC sensitive regime. For the days with O3 mixing ratios greater than
70 ppbv, the transit from VOC sensitive to NOx sensitive
1
TexAQS2000
TRAMP2006
SHARP2009
0.6
VOC
sensitive
0.4
NOx
sensitive
8-hr O3<50 ppbv
0.6
0.4
0.2
0
6:00
8-hr O3>70 ppbv
0.8
LN/Q
0.8
LN/Q
[36] The measurements performed during SHARP in
spring of 2009 provided another excellent opportunity to test
our understanding of photochemistry in this urban environment. A few highlights from this study are listed below.
[37] First, the five photochemical mechanisms (RACM2,
CB05, LaRC, SAPRC-07, and MCM) tested in this study
exhibited similar diurnal variations of the modeled HOx as
the measurements, with maxima in the midday and minima
at night. Comparing the measured HOx to the averaged
modeled HOx in the five mechanisms, the measured and
modeled OH agree quite well with an overall median
measured-to-modeled ratio of 1.13. For HO2, the measurements were consistently higher than that predicted by the
box model with an overall median measured-to-modeled
HO2 ratio of 1.45. The model underpredicted both nighttime
OH and HO2, indicating incomplete HOx sources and/or
sinks in the model. The NO dependence of measured-tomodeled OH and HO2 ratios suggests that the model
predicted OH well during the day but underpredicted HO2
with NO levels greater than a few ppbv, indicating incorrect
OH-HO2 cycling at high NO in the model.
[38] Second, the photolysis of HONO was a major HOx
source in the early morning. During the midday, O3
photolysis became a major HOx source, with significant
contributions from the photolysis of HONO and OVOCs.
Nighttime HOx production was mainly from O3 reactions
with alkenes. OH reaction with NO2 was a dominant HOx
loss process, while the self-reactions among OH, HO2, and
RO2 became important HOx loss processes in the afternoon
when these species reached their peak levels.
[39] Third, because the modeled HO2 is less than the measured HO2 especially at high NO levels, the cumulative
HO2
2
PðO3 ÞHO
mod is less than the cumulative PðO3 Þobs by a factor
of 1.4 on average. This is roughly consistent with the difference in the modeled P(O3) and the P(O3) measured by the
LN/Q=0.5
1
Summary
0.2
9:00
12:00
15:00
18:00
0
6:00
9:00
12:00
15:00
18:00
Time of day (CST)
Time of day (CST)
Figure 9. Left: median diurnal profiles of LN/Q in TEXAQS 2000, TRAMP 2006, and SHARP 2009.
The dashed line indicates a LN/Q value of 0.5, which separates the VOC-sensitive and NOx-sensitive regimes. Right: median diurnal profiles of LN/Q in SHARP 2009 for high ozone days with 8 h ozone mixing
ratios greater than 70 ppbv and low ozone days with 8 h ozone mixing ratios less than 50 ppbv.
5778
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
MOPS, which is completely independent of the OH and
HO2 measurements. The difference indicates possible
incomplete chemistry in the chemical mechanisms and thus
has implications for the ability of air quality models to accurately predict O3 production rates.
[40] Fourth, similar to the results during TexAQS 2000
and TRAMP 2006, two summertime studies in Houston,
the springtime O3 production rates during SHARP were
VOC sensitive in the morning and NOx sensitive in the afternoon, and experienced a longer NOx-sensitive period than
TexAQS 2000 and TRAMP 2006. The MOPS measurements suggest that during SHARP, the amount of O3 produced in the NOx-sensitive regime was about twice of what
was produced in the VOC-sensitive regime, indicating that
NOx control may be an efficient approach for the O3 control
in springtime for Houston.
[41] The results from SHARP have provided additional
support for regulatory actions to reduce NOx and reactive
VOCs in Houston and other cities in order to reduce O3
and other secondary pollutants, which is essential to meet
the future primary and secondary National Ambient Air
Quality Standards for O3.
[42] Acknowledgments. The authors thank Houston Advanced
Research Center (HARC) and Texas Commission for Environmental Quality (TCEQ) through Air Quality Research Program (AQRP) at University of
Texas-Austin for funding, other SHARP participating groups for the use of
their data in the study, and W. Goliff for providing the RACM2 mechanism.
Although this article has been subject to the reviews by TCEQ and NOAA
Air Resources Laboratory, it does not necessarily reflect the views of the
Agencies and no official endorsement should be inferred.
References
Alicke, B., A. Geyer, A. Hofzumahaus, F. Holland, S. Konrad, H. W. Patz,
J. Schafer, J. Stutz, A. Volz-Thomas, and U. Platt (2003), OH formation
by HONO photolysis during the BERLIOZ experiment, J. Geophys. Res.,
108(D4), 8247, doi:10.1029/2001JD000579.
Berkowitz, C. M., T. Jobson, G. Jiang, C. W. Spicer, and P. V. Doskey
(2004), Chemical and meteorological characteristics associated with rapid
increases of O3 in Houston, Texas, J. Geophys. Res., 109(D10), D10307,
doi:10.1029/2003JD004141.
Bloss, C., et al. (2005), Development of a detailed chemical mechanism
(MCMv3.1) for the atmospheric oxidation of aromatic hydrocarbons,
Atmos. Chem. Phys., 5(3), 641–664, doi:10.5194/acp-5-641-2005.
Cantrell, C. A., et al. (2003), Peroxy radical behavior during the Transport
and Chemical Evolution over the Pacific (TRACE-P) campaign as
measured aboard the NASA P-3B aircraft, J. Geophys. Res., 108(D20),
8797, doi:10.1029/2003JD003674.
Carter, W. P. L. (2007), Development of the SAPRC-07 chemical mechanism and updated ozone reactivity scales, Final Report to the California
Air Resources Board, Contract No. 03–318 (www.engr.ucr.edu/~carter/
SAPRC/saprc07.pdf).
Cazorla, M., and W. H. Brune (2010), Measurement of ozone production
sensor, Atmos. Meas. Tech., 3(3), 545–555, doi:10.5194/amt-3-545-2010.
Cazorla, M., W. H. Brune, X. Ren, and B. Lefer (2012), Direct measurement of ozone production rates in Houston in 2009 and comparison with
two estimation methods, Atmos. Chem. Phys., 12(2), 1203–1212,
doi:10.5194/acp-12-1203-2012.
Chen, S., X. Ren, J. Mao, Z. Chen, W. H. Brune, B. Lefer, B. Rappenglück,
J. Flynn, J. Olson, and J. H. Crawford (2010), A comparison of chemical
mechanisms based on TRAMP-2006 field data, Atmos. Environ., 44(33),
4116–4125, doi:10.1016/j.atmosenv.2009.05.027.
Crawford, J., et al. (1999), Assessment of upper tropospheric HOx source
over the tropical Pacific based on NASA GTE/PEM data: Net affect on
HOx and other photochemical parameters, J. Geophys. Res., 104(D13),
16,255–16,273, doi:10.1029/1999JD900106.
Crounse, J. D., F. Paulot, H. G. Kjaergaard, and P. O. Wennberg (2011),
Peroxy radical isomerization in the oxidation of isoprene, Phys. Chem.
Chem. Phys., 13(30), 13,607–13,613, doi:10.1039/C1CP21330J.
Dusanter, S., et al. (2009), Measurements of OH and HO2 concentrations
during the MCMA-2006 field campaign—Part 2: Model comparison and
radical budget, Atmos. Chem. Phys., 9(18), 6655–6675, doi:10.5194/acp9-6655-2009.
Ehhalt, D. H. (1999), Photooxidation of trace gases in the troposphere,
Phys. Chem. Chem. Phys., 1(24), 5401–5408, doi:10.1039/A905097C.
Faloona, I. C., et al. (2004), A laser-induced fluorescence instrument
for detecting tropospheric OH and HO2: Characteristics and calibration,
J. Atmos. Chem., 47(2), 139–167, doi:10.1023/B:JOCH.0000021036.53185.0e.
Finlayson-Pitts, B. J., and J. Pitts (2000), Chemistry of the Upper and Lower
Atmosphere: Theory, Experiments and Applications, pp. 264–276,
Academic Press, San Diego, California.
Fuchs, H., B. Bohn, A. Hofzumahaus, F. Holland, K. D. Lu, S. Nehr,
F. Rohrer, and A. Wahner (2011), Detection of HO2 by laser-induced
fluorescence: calibration and interferences from RO2 radicals, Atmos.
Meas. Tech., 4(6), 1209–1225, doi:10.5194/amt-4-1209-2011.
Goliff, W. S., W. R. Stockwell, and C. V Lawson (2013), The regional
atmospheric chemistry mechanism, version 2, Atmos. Environ., 68,
174–185, doi:10.1016/j.atmosenv.2012.11.038.
Hard, T. M., R. J. O’Brian, C. Y. Chan, and A. A. Mehrabzadeh (1984),
Tropospheric free radical determination by FAGE, Environ. Sci. Technol.,
18, 768–777, doi:10.1021/es00128a009.
Hofzumahaus, A., et al. (2009), Amplified trace gas removal in the
troposphere, Science, 324, 1702–1704, doi:10.1126/science.1164566.
Jenkin, M. E., S. M. Saunders, V. Wagner, and M. J. Pilling (2003),
Protocol for the development of the Master Chemical Mechanism,
MCM v3 (Part B): Tropospheric degradation of aromatic volatile organic
compounds, Atmos. Chem Phys., 3(1), 181–193, doi:10.5194/acp3-181-2003.
Jobson, B. T., M. L. Alexander, G. D. Maupin, and G. G. Muntean (2005),
On-line analysis of organic compounds in diesel exhaust using a proton
transfer reaction mass spectrometer (PTR-MS), Int. J. Mass Spectro.,
245, 78–89, doi:10.1016/j.ijms.2005.05.009.
Kanaya, Y., R. Cao, H. Akimoto, M. Fukuda, Y. Komazaki, Y. Yokouchi,
M. Koike, H. Tanimoto, N. Takegawa, and Y. Kondo (2007), Urban
photochemistry in central Tokyo: 1. Observed and modeled OH and
HO2 radical concentrations during the winter and summer of 2004, J.
Geophys. Res., 112(D21), D21312, doi:10.1029/2007JD008670.
Kanaya, Y., et al. (2012), Comparisons of observed and modeled OH
and HO2 concentrations during the ambient measurement period of the
HOxComp field campaign, Atmos. Chem. Phys., 12(5), 2567–2585,
doi:10.5194/acp-12-2567-2012.
Kleinman, L. I., P. H. Daum, Y.-N Lee, L. J. Nunnermacker,
S. R. Springston, J. Weinstein-Lloyd, and J. Rudolph (2001), Sensitivity
of ozone production rate to ozone precursors. Geophys. Res. Lett., 28,
2903–2906, doi:10.1029/2000GL012597.
Kleinman, L. I. (2005), The dependence of tropospheric ozone production
rate on ozone precursors, Atmos. Environ., 39(3), 575–586, doi:10.1016/j.
atmosenv.2004.08.047.
Konrad, S., et al. (2003), Hydrocarbon measurements at Pabstthum during
the BERLIOZ campaign and modeling of free radicals. J. Geophys.
Res., 108(D4), 8251, doi:10.1029/2001JD000866.
Kwan, A. J., A. W. H. Chan, N. L. Ng, H. G. Kjaergaard, J. H. Seinfeld,
and P. O. Wennberg (2012), Peroxy radical chemistry and OH radical
production during the NO3-initiated oxidation of isoprene, Atmos. Chem.
Phys., 12(16), 7499–7515, doi:10.5194/acp-12-7499-2012.
Lefer, B., and B. Rappengluck (2010), The TexAQS-II radical and aerosol
measurement project (TRAMP), Atmos. Environ., 44(33), 3997–4004,
doi:10.1016/j.atmosenv.2010.05.053.
Lefer, B., B. Rappengluck, J. Flynn, and C. Haman (2010), Photochemical
and meteorological relationships during the Texas-II Radical and Aerosol
Measurement Project (TRAMP), Atmos. Environ., 44(33), 4005–4013,
doi:10.1016/j.atmosenv.2010.03.011.
Lelieveld, J., et al. (2008), Atmospheric oxidation capacity sustained by a
tropical forest, Nature, 452, 737–740, doi:10.1038/nature06870.
Leuchner, M., and B. Rappenglück (2010), VOC source-receptor relationships in Houston during TexAQS-II, Atmos. Environ., 44(33),
4056–4067, doi:10.1016/j.atmosevn.200.02.029.
Liu, Z., et al. (2012), Summertime photochemistry during CAREBeijing2007: ROx budgets and O3 formation, Atmos. Chem. Phys., 12(16),
7737–7752, doi:10.5194/acp-12-7737-2012.
Lu, K. D., et al. (2012), Observation and modelling of OH and HO2
concentrations in the Pearl River Delta 2006: A missing OH source
in a VOC rich atmosphere, Atmos. Chem. Phys., 12(3), 1541–1569,
doi:10.5194/acp-12-1541-2012.
Lu, K. D., et al. (2013), Missing OH source in a suburban environment near
Beijing: Observed and modelled OH and HO2 concentrations in summer
2006, Atmos. Chem. Phys., 13(2), 1057–1080, doi:10.5194/acp-13-1057-2013.
Luke, W. T., P. Kelley, B. L. Lefer, J. Flynn, B. Rappenglück, M. Leuchner, J.
E. Dibb, L. D. Ziemba, C. H. Anderson, and M. Buhr (2010), Measurements
of primary trace gases and NOy composition in Houston, Texas, Atmos.
Environ., 44(33), 4068–4080, doi:10.1016/j.atmosenv.2009.08.014.
5779
REN ET AL.: ATMOSPHERIC PHOTOCHEMISTRY IN HOUSTON
Mao, J., et al. (2009), Airborne measurement of OH reactivity during
INTEX-B, Atmos. Chem. Phys., 9(1), 163–173, doi:10.5194/acp-9163-2009.
Mao, J., et al. (2010), Atmospheric oxidation capacity in the summer of
Houston 2006: Comparison with summer measurements in other metropolitan studies, Atmos. Environ., 44(33), 4107–4115, doi:10.1016/j.
atmosenv.2009.01.013.
Mao, J., et al. (2012), Insights into hydroxyl measurements and the atmospheric oxidation in a California forest, Atmos. Chem. Phys., 12(17),
8009–8020, doi:10.5194/acp-12-8009-2012.
Martinez, M., et al. (2003), OH and HO2 concentrations, sources, and loss
rates during the Southern Oxidants Study in Nashville, Tennessee,
summer 1999, J. Geophys. Res., 108(D19), 4617, doi:10.1029/
2003JD003551.
Mihelcic, D., et al. (2003), Peroxy radicals during BERLIOZ at Pabstthum:
Measurements, radical budgets and ozone production, J. Geophys. Res.,
108(D4), 8254, doi:10.1029/2001JD001014.
Monks, P. S. (2005), Gas-phase radical chemistry in the troposphere, Chem.
Soc. Rev., 34(5), 376–395, doi:10.1039/b307982c.
Olaguer, E. P., et al. (2009), Deciphering the role of radical precursors
during the second Texas air quality study, J. Air Waste Manag. Assoc.,
59(11), 1258–1277, doi:10.3155/1047-3289.59.11.1258.
Olson, J. R., J. H. Crawford, G. Chen, et al. (2004), Testing fast photochemical theory during TRACE-P based on measurements of OH,
HO2, and CH2O, J. Geophys. Res., 109(D15), D15S10, doi:10.1029/
2003JD004278.
Paulot, F., J. D. Crounse, H. G. Kjaergaard, A. Kürten, J. M. St. Clair,
J. H. Seinfeld, and P. O. Wennberg (2009), Unexpected epoxide formation
in the gas-phase photooxidation of isoprene, Science, 325, 730–733,
doi:10.1126/science.1172910.
Peeters, J., T. L. Nguyen, and L. Vereecken (2009), HOx radical regeneration in the oxidation of isoprene, Phys. Chem. Chem. Phys., 11(28),
5935–5939, doi:10.1039/B908511D.
Peeters, J., and J.-F. Müller (2010), HOx radical regeneration in isoprene
oxidation via peroxy radical isomerisations, II: Experimental evidence
and global impact, Phys. Chem. Chem. Phys., 12(42), 14,227–14,235,
doi:10.1039/C0CP00811G.
Ren, X., et al. (2003a), OH and HO2 chemistry in the urban atmosphere of
New York City, Atmos. Environ., 37(26), 3639–3651, doi:10.1016/
S1352-2310(03)00459-X.
Ren, X., G. D. Edwards, C. A. Cantrell, R. L. Lesher, A. R. Metcalf, T. Shirley,
and W. H. Brune (2003b), Intercomparison of peroxy radical measurements
at a rural site using laser-induced fluorescence and Peroxy Radical Chemical
Ionization Mass Spectrometer (PerCIMS) techniques, J. Geophys. Res.,
108(D19), 4605, doi:10.1029/2003JD003644.
Ren, X., W. H. Brune, C. A. Cantrell, and G. D. Edwards, T. Shirley,
A. R. Metcalf, and R. L. Lesher (2005), Hydroxyl and peroxy radical
chemistry in a rural area of Central Pennsylvania: Observations and
model comparisons, J. Atmos. Chem., 52(3), 231–-257, doi:10.1007/
s10874-005-3651-7.
Ren, X., et al. (2008), HOx chemistry during INTEX–A 2004: Observation,
model calculations and comparison with previous studies, J. Geophys.
Res., 113(D5), D05310, doi:10.1029/2007JD009166.
Ren, X., et al. (2010), Measurement of nitrous acid at Blodgett Forest during
BEARPEX2007, Atmos. Chem. Phys., 10(13), 6283–6294, doi:10.5194/
acp-10-6283-2010.
Sander, S. P., et al. (2011), Chemical kinetics and photochemical data for
use in atmospheric studies, Evaluation No. 17, JPL Publication 10–6,
Jet Propulsion Laboratory, Pasadena (http://jpldataeval.jpl.nasa.gov).
Saunders, S. M., M. E. Jenkin, R. G. Derwent, and M. J. Pilling (2003),
Protocol for the development of the Master Chemical Mechanism,
MCM v3 (Part A): Tropospheric degradation of non-aromatic volatile
organic compounds, Atmos. Chem. Phys., 3(1), 161–180, doi:10.5194/
acp-3-161-2003.
Stutz, J., H.-J. Oh, S. I. Whitlow, C. Anderson, J. E. Dibb, J. H. Flynn,
B. Rappenglück, and B. Lefer (2010a), Simultaneous DOAS and mistchamber IC measurements of HONO in Houston, TX, Atmos. Environ.,
44(33), 4090–4098, doi:10.1016/j.atmosenv.2009.02.003.
Stutz, J., K. W. Wong, L. Lawrence, L. Ziemb, J. H. Flynn,
B. Rappenglück, and B. Lefer (2010b), Nocturnal NO3 radical chemistry
in Houston, TX, Atmos. Environ., 44(33), 4099–4106, doi:10.1016/j.
atmosenv.2009.03.004.
Texas Air Quality Research Program (2010), TCEQ Priority Research Areas
(http://aqrp.ceer.utexas.edu/docs/AQR%20Strategic%20Plan%20Summary%20May%2027%202010.pdf).
Volkamer, R., P. Sheehy, L. T. Molina, and M. J. Molina (2010), Oxidative
capacity of the Mexico City atmosphere—Part 1: A radical source
perspective, Atmos. Chem. Phys., 10(14), 6969–6991, doi:10.5194/acp10-6969-2010.
Volz-Thomas, A., H. W. Pätz, N. Houben, S. Konrad, D. Mihelcic,
T. Klüpfel, and D. Perner (2003), Inorganic trace gases and peroxy
radicals during BERLIOZ at Pabstthum: An investigation of
the photostationary state of NOx and O3, J. Geophys. Res., 108(D4),
8248, doi:10.1029/2001JD001255.
Whalley, L. K., et al. (2011), Quantifying the magnitude of a missing
hydroxyl radical source in a tropical rainforest, Atmos. Chem. Phys.,
11(14), 7223–7233, doi:10.5194/acp-11-7223-2011.
Yarwood, G., S. Rao, M. Yocke, and G. Z. Whitten (2005), Updates to the Carbon Bond Mechanism: CB05, Final Report to the US EPA (RT-0400675),
(http://www.camx.com/publ/ pdfs/CB05_Final_Report_120805.pdf).
5780